{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "autoscroll": "json-false",
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "ein.tags": [
     "worksheet-0"
    ]
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/tavi/miniconda/envs/bladder2/lib/python2.7/site-packages/IPython/html.py:14: ShimWarning: The `IPython.html` package has been deprecated since IPython 4.0. You should import from `notebook` instead. `IPython.html.widgets` has moved to `ipywidgets`.\n",
      "  \"`IPython.html.widgets` has moved to `ipywidgets`.\", ShimWarning)\n"
     ]
    }
   ],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "import sys \n",
    "from os import getcwd, path\n",
    "sys.path.append(path.dirname(getcwd()))\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sb\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "autoscroll": "json-false",
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "ein.tags": [
     "worksheet-0"
    ]
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/tavi/miniconda/envs/bladder2/lib/python2.7/site-packages/rpy2/rinterface/__init__.py:185: RRuntimeWarning: Error in file(filename, \"r\") : \n",
      "  5 arguments passed to .Internal(file) which requires 6\n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/home/tavi/miniconda/envs/bladder2/lib/python2.7/site-packages/rpy2/rinterface/__init__.py:185: RRuntimeWarning: Error : unable to load R code in package ‘utils’\n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/home/tavi/miniconda/envs/bladder2/lib/python2.7/site-packages/rpy2/rinterface/__init__.py:185: RRuntimeWarning: In addition: \n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/home/tavi/miniconda/envs/bladder2/lib/python2.7/site-packages/rpy2/rinterface/__init__.py:185: RRuntimeWarning: Warning message:\n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/home/tavi/miniconda/envs/bladder2/lib/python2.7/site-packages/rpy2/rinterface/__init__.py:185: RRuntimeWarning: package \"methods\" in options(\"defaultPackages\") was not found \n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/home/tavi/miniconda/envs/bladder2/lib/python2.7/site-packages/rpy2/rinterface/__init__.py:185: RRuntimeWarning: package ‘utils’ in options(\"defaultPackages\") was not found \n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/home/tavi/miniconda/envs/bladder2/lib/python2.7/site-packages/rpy2/rinterface/__init__.py:185: RRuntimeWarning: Error : unable to load R code in package ‘grDevices’\n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/home/tavi/miniconda/envs/bladder2/lib/python2.7/site-packages/rpy2/rinterface/__init__.py:185: RRuntimeWarning: package ‘grDevices’ in options(\"defaultPackages\") was not found \n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/home/tavi/miniconda/envs/bladder2/lib/python2.7/site-packages/rpy2/rinterface/__init__.py:185: RRuntimeWarning: package ‘graphics’ in options(\"defaultPackages\") was not found \n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/home/tavi/miniconda/envs/bladder2/lib/python2.7/site-packages/rpy2/rinterface/__init__.py:185: RRuntimeWarning: package ‘stats’ in options(\"defaultPackages\") was not found \n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/home/tavi/miniconda/envs/bladder2/lib/python2.7/site-packages/rpy2/rinterface/__init__.py:185: RRuntimeWarning: During startup - \n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/home/tavi/miniconda/envs/bladder2/lib/python2.7/site-packages/rpy2/rinterface/__init__.py:185: RRuntimeWarning: package ‘methods’ in options(\"defaultPackages\") was not found \n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n"
     ]
    }
   ],
   "source": [
    "from utils import data\n",
    "from utils.paper import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "from cohorts.styling import set_styling\n",
    "set_styling()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "def expanded_clones_barplot(cohort_a_b, ax):\n",
    "    df_tcr_a_b = cohort_a_b.as_dataframe()\n",
    "    df_tcr_a_b = df_tcr_a_b.set_index(\"patient_id\", drop=False).sort_values(\n",
    "        by=\"N Expanded Clones that were TILs\")\n",
    "    import matplotlib.colors as colors\n",
    "    red = colors.hex2color(\"#bb3f3f\")\n",
    "    blue = colors.hex2color(\"#5a86ad\")\n",
    "    palette = [blue if row[\"is_benefit\"] else red for i, row in df_tcr_a_b.iterrows()]\n",
    "    plot_expanded = sb.barplot(ax=ax, data=df_tcr_a_b, x=\"patient_id\", y=\"N Expanded Clones\", \n",
    "               order=df_tcr_a_b.index, palette=palette)\n",
    "    plot_expanded_tils = sb.barplot(ax=ax, data=df_tcr_a_b, x=\"patient_id\", \n",
    "               order=df_tcr_a_b.index,\n",
    "               y=\"N Expanded Clones that were TILs\", color=\"orange\")\n",
    "    import matplotlib.patches as mpatches\n",
    "    import matplotlib.pyplot as plt\n",
    "    no_benefit_patch = mpatches.Patch(color=red, label=\"No \" + cohort.benefit_plot_name)\n",
    "    benefit_patch = mpatches.Patch(color=blue, label=cohort.benefit_plot_name)\n",
    "    til_patch = mpatches.Patch(color=\"orange\", label=\"# Exp. TIL Clones\")\n",
    "    plot_expanded.set_xticklabels(plot_expanded.xaxis.get_majorticklabels(), rotation=80)\n",
    "    plot_expanded.set_xlabel(\"Subject ID\")\n",
    "    plot_expanded.set_ylabel(\"# Expanded Clones\")\n",
    "    plot_expanded.legend(handles=[benefit_patch, no_benefit_patch, til_patch],\n",
    "                         bbox_to_anchor=(0, 1), loc=2, borderaxespad=0, prop={'size':13})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/tavi/miniconda/envs/bladder2/lib/python2.7/site-packages/matplotlib/font_manager.py:1297: UserWarning: findfont: Font family [u'sans-serif'] not found. Falling back to DejaVu Sans\n",
      "  (prop.get_family(), self.defaultFamily[fontext]))\n"
     ]
    },
    {
     "data": {
      "image/png": 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CAGAiFAAAE6EAAJgIBQDARCgAACZCAQAwEQoAgIlQAABMhAIAYCIUAAAToQAAmAgFAMBE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\nWmi29QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff0f1c3ead0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax_null = plt.subplots()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "def clonality_proportion_dcb_plot(ax=None):\n",
    "    if ax is None:\n",
    "        ax = plt.gca()\n",
    "        \n",
    "    results_clonality = cohort.plot_benefit(on=\"Clonality\", ax=ax_null)\n",
    "    clonality_significant = results_clonality.p_value <= 0.05\n",
    "    results_fraction = cohort.plot_benefit(on=\"T-cell fraction\", ax=ax_null)\n",
    "    fraction_significant = results_fraction.p_value <= 0.05\n",
    "    \n",
    "    cols, df_clonality_fraction_init = cohort.as_dataframe(on={\"TIL Clonality\": \"Clonality\", \n",
    "                                                               \"TIL Proportion\": \"T-cell fraction\"},\n",
    "                                                      return_cols=True)\n",
    "    df_clonality_fraction_benefit = df_clonality_fraction_init[[\"patient_id\", \"benefit\"]].set_index(\"patient_id\")\n",
    "    df_clonality_fraction = df_clonality_fraction_init[cols + [\"patient_id\"]]\n",
    "    df_clonality_fraction.set_index(\"patient_id\", inplace=True)\n",
    "    df_clonality_fraction = pd.DataFrame(df_clonality_fraction.unstack())\n",
    "    df_clonality_fraction[\"TIL Measurement\"] = df_clonality_fraction.index.get_level_values(0)\n",
    "    df_clonality_fraction.columns = [\"Percent\", \"TIL Measurement\"]\n",
    "    df_clonality_fraction = df_clonality_fraction.join(df_clonality_fraction_benefit)\n",
    "    df_clonality_fraction[\"Response\"] = df_clonality_fraction.benefit.apply(\n",
    "        lambda b: cohort.benefit_plot_name if b else \"No \" + cohort.benefit_plot_name)\n",
    "\n",
    "    def add_significance_indicators(plot, indicators=[]):\n",
    "        from cohorts.plot import vertical_percent\n",
    "        plot_bottom, plot_top = plot.get_ylim()\n",
    "        # Give the plot a little room for the significance indicator\n",
    "        line_height = vertical_percent(plot, 0.1)\n",
    "        # Add some extra spacing below the indicator\n",
    "        plot_top = plot_top + line_height\n",
    "        # Add some extra spacing above the indicator\n",
    "        plot.set_ylim(top=plot_top + line_height * 2)\n",
    "        color = \"black\"\n",
    "        line_top = plot_top + line_height\n",
    "        for col_a, col_b, significant in indicators:\n",
    "            plot.plot([col_a, col_a, col_b, col_b], [plot_top, line_top, line_top, plot_top], lw=1.5, color=color)\n",
    "            indicator = \"*\" if significant else \"ns\"\n",
    "            plot.text((col_a + col_b) * 0.5, line_top, indicator, ha=\"center\", va=\"bottom\", color=color)\n",
    "    \n",
    "    box_ax = sb.boxplot(data=df_clonality_fraction, y=\"Percent\", x=\"TIL Measurement\", hue=\"Response\",\n",
    "                         ax=ax)\n",
    "    # http://stackoverflow.com/questions/35538882/seaborn-boxplot-stripplot-duplicate-legend\n",
    "    strip_ax = sb.stripplot(data=df_clonality_fraction, jitter=0.05, palette={cohort.benefit_plot_name: \"0.3\", \n",
    "                                                                              (\"No \" + cohort.benefit_plot_name): \"0.3\"}, split=True, y=\"Percent\", x=\"TIL Measurement\", hue=\"Response\",\n",
    "                         ax=ax)\n",
    "    \n",
    "    add_significance_indicators(ax, [(-0.2, 0.2, clonality_significant), (0.8, 1.2, fraction_significant)])\n",
    "    \n",
    "    handles, labels = ax.get_legend_handles_labels()\n",
    "    ax.legend_.remove()\n",
    "    l = ax.legend(handles[0:2], labels[0:2], bbox_to_anchor=(0, 0.7), loc=2, borderaxespad=0.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "def update_styling():\n",
    "    import matplotlib as mpl\n",
    "    mpl.rcParams.update({\"legend.fontsize\": 15})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "inner join with tcr_tumor: 29 to 24 rows\n",
      "inner join with tcr_tumor: 29 to 24 rows\n",
      "{'dataframe_hash': -2467646966976180658,\n",
      " 'provenance_file_summary': {u'cohorts': u'0.4.0+3.gda968fb',\n",
      "                             u'isovar': u'0.0.6',\n",
      "                             u'mhctools': u'0.3.0',\n",
      "                             u'numpy': u'1.11.1',\n",
      "                             u'pandas': u'0.18.1',\n",
      "                             u'pyensembl': u'1.0.3',\n",
      "                             u'scipy': u'0.18.1',\n",
      "                             u'topiary': u'0.1.0',\n",
      "                             u'varcode': u'0.5.10'}}\n",
      "inner join with tcr_tumor: 29 to 24 rows\n",
      "Mann-Whitney test: U=91.0, p-value=0.104634955402 (two-sided)\n",
      "inner join with tcr_tumor: 29 to 24 rows\n",
      "Mann-Whitney test: U=97.0, p-value=0.0465677613869 (two-sided)\n",
      "inner join with tcr_tumor: 29 to 24 rows\n",
      "inner join with tcr_tumor: 29 to 24 rows\n",
      "inner join with tcr_tumor: 29 to 24 rows\n",
      "< Median TIL Proportion or\n",
      " < Median TIL Clonality  False  True \n",
      "Response                                                        \n",
      "DCB                                                     6      2\n",
      "No DCB                                                  3     13\n",
      "Fisher's Exact Test: OR: 13.0, p-value=0.0214882707816 (two-sided)\n",
      "inner join with tcr_peripheral_a: 29 to 29 rows\n",
      "inner join with tcr_peripheral_a: 29 to 29 rows\n",
      "{'dataframe_hash': -8062678075537494193,\n",
      " 'provenance_file_summary': {u'cohorts': u'0.4.0+3.gda968fb',\n",
      "                             u'isovar': u'0.0.6',\n",
      "                             u'mhctools': u'0.3.0',\n",
      "                             u'numpy': u'1.11.1',\n",
      "                             u'pandas': u'0.18.1',\n",
      "                             u'pyensembl': u'1.0.3',\n",
      "                             u'scipy': u'0.18.1',\n",
      "                             u'topiary': u'0.1.0',\n",
      "                             u'varcode': u'0.5.10'}}\n",
      "inner join with tcr_peripheral_a: 29 to 29 rows\n",
      "# no condition 15\n",
      "# with condition 14\n",
      "inner join with tcr_peripheral_a: 29 to 29 rows\n",
      "# no condition 15\n",
      "# with condition 14\n",
      "inner join with tcr_peripheral_a: 29 to 29 rows\n",
      "Mann-Whitney test: U=41.0, p-value=0.00612886249432 (two-sided)\n",
      "inner join with tcr_peripheral_a: 29 to 29 rows\n",
      "Mann-Whitney test: U=65.0, p-value=0.248114557042 (two-sided)\n",
      "inner join with tcr_expansion_a_b: 29 to 22 rows\n",
      "inner join with tcr_expansion_a_b: 29 to 22 rows\n",
      "{'dataframe_hash': -3708790230929705357,\n",
      " 'provenance_file_summary': {u'cohorts': u'0.4.0+3.gda968fb',\n",
      "                             u'isovar': u'0.0.6',\n",
      "                             u'mhctools': u'0.3.0',\n",
      "                             u'numpy': u'1.11.1',\n",
      "                             u'pandas': u'0.18.1',\n",
      "                             u'pyensembl': u'1.0.3',\n",
      "                             u'scipy': u'0.18.1',\n",
      "                             u'topiary': u'0.1.0',\n",
      "                             u'varcode': u'0.5.10'}}\n",
      "inner join with tcr_expansion_a_b: 29 to 22 rows\n",
      "inner join with tcr_expansion_a_b: 29 to 22 rows\n",
      "Mann-Whitney test: U=89.5, p-value=0.0224798103147 (two-sided)\n",
      "{{{figure_tcr}}}\n"
     ]
    },
    {
     "data": {
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TTz9h165d+Pbbb/H48WNMmzYNCoVC45iIDMWTJ0/g5eWF2rVro3///sqyihg/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p3E6tWrn+hvbGysmDhxoggKChLu7u7Cz89PfPDBB9K+pZrGdfjwYTF37lzRoUMH0bZtWzFs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\nAIiJUA0AAADE9BMz74VPXJ4qkgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff0ee823a10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axarr = plt.subplots(4, 2)\n",
    "fig.set_size_inches(2250 / 225, 2625 / 225)\n",
    "\n",
    "title_loc = \"left\"\n",
    "title_fontsize = 18\n",
    "title_kwargs = {\"loc\": title_loc, \"fontsize\": title_fontsize, \"fontweight\": \"bold\"}\n",
    "\n",
    "cohort = data.init_cohort(join_with=\"tcr_tumor\",\n",
    "                          exclude_patient_ids=set(),\n",
    "                          only_patients_with_bams=False)\n",
    "\n",
    "\"\"\"\n",
    "Removed for now.\n",
    "\n",
    "df = cohort.as_dataframe([\"Clonality\", \"T-cell fraction\"])\n",
    "results = cohort.plot_correlation(on={\"TIL Clonality\": \"Clonality\", \"TIL Proportion\": \"T-cell fraction\"}, x_col=\"TIL Clonality\", \n",
    "                          plot_type=\"regplot\",\n",
    "                          plot_kwargs={\"ax\": axarr[0,0],\n",
    "                                       \"fit_reg\": False,\n",
    "                                       \"scatter_kws\": {\"s\": 200,\n",
    "                                       \"c\": [\"green\" if benefit else \"red\" for benefit in df.is_benefit]}})\n",
    "results.plot.set_xlim((0, 0.4))\n",
    "results.plot.set_ylim((0, 0.4))\n",
    "results.plot.set_title(\"A\", **title_kwargs)\n",
    "\"\"\"\n",
    "\n",
    "update_styling()\n",
    "clonality_proportion_dcb_plot(ax=axarr[0,0])\n",
    "axarr[0,0].set_title(\"A\", **title_kwargs)\n",
    "\n",
    "df_til = cohort.as_dataframe()\n",
    "def below_either_median(row):\n",
    "    either = ((row[\"Clonality\"] < df_til[\"Clonality\"].median()) or \n",
    "              (row[\"T-cell fraction\"] < df_til[\"T-cell fraction\"].median()))\n",
    "    return either\n",
    "cohort.plot_benefit({\"< Median TIL Proportion or\\n < Median TIL Clonality\": below_either_median},\n",
    "                                                     ax=axarr[0,1])\n",
    "\n",
    "labels = [label.get_text() for label in axarr[0,1].get_yticklabels()]\n",
    "update_styling()\n",
    "ylabel = axarr[0,1].get_ylabel()\n",
    "axarr[0,1].set_ylabel(ylabel, fontsize=12)\n",
    "axarr[0,1].set_title(\"B\", **title_kwargs)\n",
    "# Hide 1.25 for the sig indiciator\n",
    "axarr[0,1].set_yticklabels([\"0.0\", \"\", \"0.5\", \"\", \"1.0\", \"\"])\n",
    "\n",
    "cohort = data.init_cohort(join_with=\"tcr_peripheral_a\",\n",
    "                          exclude_patient_ids=set(),\n",
    "                          only_patients_with_bams=False)\n",
    "\n",
    "cohort.tcr_peripheral_a_clonality_short_plot_name = \"Pre-tx Clon.\\n\"\n",
    "\n",
    "update_styling()\n",
    "import matplotlib as mpl\n",
    "mpl.rcParams.update({\"legend.fontsize\": 13})\n",
    "cohort.plot_survival(on={cohort.tcr_peripheral_a_clonality_short_plot_name: \"Clonality\"}, how=\"pfs\", ax=axarr[1,0])\n",
    "ax=axarr[1,0].set_title(\"C\", **title_kwargs)\n",
    "axarr[1,0].set_yticklabels([0, 20, 40, 60, 80, 100])\n",
    "\n",
    "update_styling()\n",
    "import matplotlib as mpl\n",
    "mpl.rcParams.update({\"legend.fontsize\": 13})\n",
    "cohort.plot_survival(on={cohort.tcr_peripheral_a_clonality_short_plot_name: \"Clonality\"}, how=\"os\", ax=axarr[1,1])\n",
    "ax=axarr[1,1].set_title(\"D\", **title_kwargs)\n",
    "axarr[1,1].legend(loc='lower left')\n",
    "axarr[1,1].set_yticklabels([0, 20, 40, 60, 80, 100])\n",
    "\n",
    "cohort.tcr_peripheral_a_clonality_short_plot_name = \"Pre-tx Clon.\"\n",
    "\n",
    "cohort.plot_benefit_os(on={cohort.tcr_peripheral_a_clonality_short_plot_name: \"Clonality\"}, ax=axarr[2,0])\n",
    "ax=axarr[2,0].set_title(\"E\", **title_kwargs)\n",
    "\n",
    "cohort.plot_benefit(on={cohort.tcr_peripheral_a_clonality_short_plot_name: \"Clonality\"}, ax=axarr[2,1])\n",
    "ax=axarr[2,1].set_title(\"F\", **title_kwargs)\n",
    "\n",
    "cohort_tcr_a_b = data.init_cohort(join_with=\"tcr_expansion_a_b\", \n",
    "                          exclude_patient_ids=set(),\n",
    "                          only_patients_with_bams=False)\n",
    "\n",
    "expanded_clones_barplot(cohort_a_b=cohort_tcr_a_b, ax=axarr[3,0])\n",
    "ax=axarr[3,0].set_title(\"G\", **title_kwargs)\n",
    "\n",
    "cohort_tcr_a_b.plot_benefit(\n",
    "        {\"# Expanded TIL Clones\": \"N Expanded Clones that were TILs\"}, ax=axarr[3,1])\n",
    "ax=axarr[3,1].set_title(\"H\", **title_kwargs)\n",
    "\n",
    "plt.subplots_adjust(bottom=-0.5)\n",
    "plt.subplots_adjust(left=-0.01)\n",
    "plt.subplots_adjust(wspace=0.3)\n",
    "plt.subplots_adjust(hspace=0.3)\n",
    "\n",
    "hyper_figure_label_printer(\"figure_tcr\")\n",
    "\n",
    "fig.savefig(path.join(data.REPO_DATA_DIR, 'Fig1.tif'), format='tif', dpi=300, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "from utils.paper import resize_image_plos\n",
    "resize_image_plos(\"Fig1.tif\", \"Fig1.tif\", figure_path=data.REPO_DATA_DIR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [conda env:bladder2]",
   "language": "python",
   "name": "conda-env-bladder2-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  },
  "name": "TCR Clonality.ipynb"
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
